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Object detection in aerial images using DOTA dataset: A survey
International Journal of Applied Earth Observation and Geoinformation ( IF 7.6 ) Pub Date : 2024-10-20 , DOI: 10.1016/j.jag.2024.104208
Ziyi Chen, Huayou Wang, Xinyuan Wu, Jing Wang, Xinrui Lin, Cheng Wang, Kyle Gao, Michael Chapman, Dilong Li

In recent years, the Dataset for Object deTection in Aerial images (DOTA) dataset has played a pivotal role in advancing object detection in aerial images (ODAI). Despite its significance, there hasn’t been a comprehensive review summarizing its research developments. Addressing this gap, this paper offers the first comprehensive overview on the subject. Within this review, we begin by examining prevalent object detection datasets of natural scene images alongside object detection datasets of remote sensing images (RSIs). We then present an in-depth comparative analysis between these datasets and the DOTA dataset, supported by numerous charts and tables. We proceed to outline both traditional techniques for ODAI and methods rooted in deep learning. Subsequently, we provide a recap of the latest advancements in the field achieved using the DOTA dataset. Concluding our review, we delve into the current challenges facing ODAI and propose potential future research directions.

中文翻译:


使用 DOTA 数据集在航拍图像中进行目标检测:一项调查



近年来,航空影像中目标检测数据集 (DOTA) 数据集在推进航空影像中的目标检测 (ODAI) 方面发挥了关键作用。尽管它很重要,但还没有全面的综述来总结其研究进展。为了解决这一差距,本文首次对该主题进行了全面概述。在这篇综述中,我们首先检查了自然场景图像的普遍对象检测数据集以及遥感图像 (RSI) 的对象检测数据集。然后,我们提出了这些数据集与 DOTA 数据集之间的深入比较分析,并得到了大量图表和表格的支持。我们继续概述了 ODAI 的传统技术和植根于深度学习的方法。随后,我们回顾了使用 DOTA 数据集实现的该领域的最新进展。总结我们的综述,我们深入研究了 ODAI 当前面临的挑战,并提出了潜在的未来研究方向。
更新日期:2024-10-20
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